Psychometric Intelligence, Coalition Formation and Domain-Specific Adaptation

The remarkable intricacy of human general intelligence has so far left psychologists being unable to agree on its common definition. The framework definition of general human intelligence, suitable for a discussion herein and as proposed by an artificial intelligence researcher David L. Poole, is that intelligence is wherein “an intelligent agent does what is appropriate for its circumstances and its goal, it is flexible to changing environments and changing goals, it learns from experience, and it makes appropriate choices given perceptual limitations and finite computation”. Learning from past experiences and adapting behavior accordingly have been vital for an organism in order to prevent its distinction or endangerment in a dynamic competing environment. The more phenotypically intelligent an organism is the faster it can learn to apply behavioral changes in order to survive and the more prone it is to produce more surviving offspring. This applies to humans as it does to all intelligent agents, or species.

Furthermore, throughout the history of life, humans have adapted even more effectively to different habitats in all kinds of environmental conditions when they formed collaborative groups, or adaptation coalitions. In evolutionary psychology, coalitions are perceived as groups of interdependent individuals (or organizations) that form alliances around stability and survivability in order to achieve common desired goals that the established community is willing to pursue. There is an unambiguous evolutionary basis for this phenomenon among intelligent agents. In a dynamic environment, no single individual acting alone can influence optimal outcomes of a specific problem nor accomplish as many tasks required for ensuring one’s survivability systematically, through multitudinous generations. As a result, increased intelligence has been functional in humans' ancestral past by tracking rapid rates of environmental change and accelerating one’s adaptation rate by initiating coalition formation in competing evolutionary strategies. Specifically, the term of ‘intelligence’ in terms of proactive collation formation is referred herein to ‘psychometric intelligence’, the human cognitive abilities’ level differences evaluated quantitatively on the basis of performance in cognitive ability tests.

Therefore, this essay accentuates the principal adaptive hypothesis that intelligent agents, namely humans, serve as catalysts to increase multidisciplinary collaboration in the form of a coalition as a domain specific adaptation to evolutionary novelty. Specifically, that humans that possess higher psychometric intelligence are statistically more prone to preemptively form a coalition as an adaptation measure to cope with dynamic events in the environment change.

But before this essay argues for the above claim, it will be necessary to explain what the evolutionary-psychological view of the psychometric intelligence and the domain-specific adaptation is.

Individual differences among humans in their cognitive abilities have been of long-lasting controversy. Studies have conceptualized intelligence as a single operational entity that can be identified, assessed and quantified via cognitive task-testing tools, wherein “a person’s score on a statistically determined set of questions”, or “Intelligence is what the intelligence test measures”. Various evolutionary-psychological theories of intelligence have suggested that physical reaction efficiency and data processing speed constitute a proper definition for intelligence, fundamentally structured around acquiring sensory input from the environment and then interpreting and organizing it by the brain. Consequently, a human brain has been referenced in its exemplary function to a computer, in that both are types of computing machines generating complex patterns of output, after dissemination of correlating complex patterns of input, and after querying to stored information. In what follows, this essay assumes that intelligence can be thus tested and quantified in computational terms. And while psychometric cognitive ability tests do not encapsulate all the capabilities of humans, from the evolutionary point of view, studies have shown that cognitive intelligence indicate genetic quality of a phenotype expressed in sexual and social selection levels. Moreover, the genetic factor of cognitive ability level differences in human intelligence is then evolutionary likely to be related to the individual’s ability to form a coalition, which generates adaptive behaviors. This theory is widely-agreed upon.

Furthermore, evolutionary psychologists adopt positions that look into intelligence as a domain-general structure, or a non-modular architecture, not designed to solve any specific problem from the human evolutionary past, versus domain-specific, or constantly heuristic, designed by natural selection for solving any computational problems by exploiting “…transient or novel local conditions to achieve adaptive outcomes”. These two approaches refer to intelligence as a myriad of special-purpose modules shaped by natural selection to function as a problem-solving apparatus, wherein the latter form is employed whenever an allocated special-purpose module does not exist to solve a particular problem that confronted our prehistoric predecessors.

Thus, the position that psychometric intelligence serves in coalition formation as a domain-specific adaption is adopted here. Our mind is not composed of "general-purposes" mechanisms, such as a general-purpose reasoning mechanism or a general-purpose learning mechanism, but instead consists of hundreds or thousands of highly specialized modules that provide us with flexible knowledge and flexible abilities in various sporadic domains. Most of these modules constitute a variant human nature and have not evolved during specific human development time in Pleistocene hunter-gatherer societies, applying universality over all human population. Coalition formation, similar to language development or free-rider detection, does not emerge from the combination of wide cognitive processes but rather from a domain specific adaptation, providing further support for the theory of this essay, that stems from cognitive ability influence on timing factors of coalition formation.

Unlocking the causal relationships between individual psychometric intelligence and initiating coalition formation could delineate multiple cognitive mechanisms, integrating evolutionary psychology with any other aspect of differential psychology in the vein of intrasexual, intersexual, intercultural or intergenerational competition.

This essay seeks to propose examination of correlation between cognitive ability scores (which for simplicity, uniformity and evidence availability uses well-known intelligence quotient (IQ) test scores, but in theory can include specifically designed assessment tests) and an individual’s initiation of coalition formation. Specifically, the correlation could be scrutinized via the adaption features of coalition formation as a part of an (expected) individual’s participation in warfare, or a warfare-like simulation.

Employing more modern forms of coalition formation (for example, trying to correlate IQ test scores of the original founders of private and public companies and their initiation ability to form a coalition) would have to ignore many important environmental factors, such as individual wealth and its origin, national technological and scientific progress of founders’ countries, and local business and capital policies – all of which can be unified under ‘environmental opportunity factors’ yet cannot be empirically isolated nor estimated in a coalition-driven dynamic.

In warfare, however, the existence of psychological adaptations for some aspects of coalitional formation and cooperation is evident: “Coalitional aggression evolved because it allowed participants in such coalitions to promote their fitness by gaining access to disputed reproduction enhancing resources that would otherwise be denied to them”. Here the hypothesis does not test whether humans possessing higher psychometric intelligence have evolved specific psychological adaptations for warfare, but rather try to identify whether humans possessing higher psychometric intelligence are more prone to initiate coalition formation as a domain-specific adaptation using warfare-like simulation as a trigger.

Since IQ-type tests are believed to remain chronologically constant through one’s life and due to the abundance of IQ correlational studies pointing at social performance factors (education, occupation, income, and imprisonment), it is assumed here that cognitive ability test in a form of IQ score is a viable predictor of human intelligence. And while, beyond any doubt, environmental factors are source of differences, holding environmental and genetic influences on psychometric intelligence differences constant, could allow to check the robustness effect of correlation between psychometric intelligence and coalition formation initiation.

To test this model, intergroup coalition formation can be methodically reviewed in the selection process of various Special Forces Assessment and Selection (SFAS) courses around the world. A SFAS course is usually a few days or weeks long and utilizes a more vigorous (than other military units) individual- and group-focused assessment process that is designed to select candidates who are capable of meeting physical and psychological requirements close to the operational combat environments and suitable for future service in the special forces units. The selection process is objective-, subjective- and performance-, behavior-based. As a part of conducted evaluation, candidates are subjected behaviorally to warfare scenarios wherein coalition formation is required. During this initiation phase, an adaptation test could be designed to produce observable and measurable data that can be later related to the individual’s psychometric intelligence.

Furthermore, depending on the country where the SFAS course is performed, additional environmental factors (aggregated life history indicators) can be controlled, including intrasexual, intersexual, intercultural or intergenerational comparison. Women in various armies across the world (US Navy's SEAL, UK Special Reconnaissance Regiment, Norway’s Jegertroppen, Israel’s Air Force and others) are permitted to apply to join, partake in SFAS courses and serve in those units. Candidates from different countries go through a dedicated SFAS course to join Groupe de Commandos Parachutistes (GCP), an elite unit that is a part of the French Foreign Legion, uniquely established for foreign recruits, willing to serve in the French Armed Forces. Lastly, various environmental factors in intergenerational differences can be tested across numerous special forces units (for example, while Israeli Special Forces perform SFAS courses strictly ahead of the candidate’s legal drafting age of 18, US Navy's SEAL and UK Special Reconnaissance Regiment comprise on average much older participants).

The test can be structured around at least one intrasexual source of evidence in a form of observable data provided by a course board who holistically identifies, assesses and selects one or more candidates that initiate coalition formation to solve a simulated problem during various combat exercises. Moreover, as described above, such data collection can be repeated and applied across different units, tuning necessary environmental factors such as sex, age and cultural differences. Collaborative multisite studies can be performed, in which multiple researchers cooperate to conduct the same study at multiple sites to increase sample size and data pool. Once the data is collected, it can be connected to a specific subject’s IQ score and test whether the stated theory is correct, namely whether correlation exists between higher psychometric intelligence and coalition formation initiation.

Additionally, as a second source of evidence, a cross-species analysis based on the construction of a designated cognitive ability test, could be employed to test whether other species in nature (for example chimpanzees or pigeons) have the ability to form preemptive collaborative alliances as a part of preparation to an intergroup or cross-group conflict. The theory in a cross-species analysis is expected to be consistent with that of humans, wherein individual differences in psychometric intelligence are correlated to the likeliness of initiating coalition formation hence constitute an adaptation measure to cope with the environment change.

Lastly, as a third source of evidence, changing a unifying goal of coalition formation (for example as in forming a new political party or a studying group rather than warfare) can provide further insights into the evolutionary-psychological tendencies as a domain-specific adaptation. However, the estimated correlation results are believed to be inconclusive in that case, as they would increasingly rely on numerous additional environmental differences and would be muted in the adaptation survivability-related effect.

The gathered evidence from these tests can point at new possibilities for better understanding the interrelationship mechanisms between cognitive abilities and coalitions and establish a stronger collaboration across various psychological disciplines in understanding human intelligence differences.

Improvisational Intelligence as a Domain-Specific Adaptation

Intelligence is what you use when you don't know what to do.

― Jean Piaget

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The human brain is remarkable in its complexity design. A myriad of constantly evolving, reciprocally sophisticated computational systems, engineered by natural selection to use information to adaptively regulate physiology, behavior and cognition. Our brain defines our humanity. Systematically, through multitudinous generations, both the human brain structure (hardware) and its neural algorithms (software) have been fine-tuned by evolution to enable us adapt better to environment.

For an extended period of time, the structural elements of the human brain, such as size and shape, proved to resemble more closely to those of the rest members in the Hominidae family.  Albeit, starting with specimen of Australopithecus afarensis, the brain has began to evolve and transfigure. It increased in size and developed new areas. The main dissimilarity was the development of the neocortex, the frontal and prefrontal cortex ― today these areas are associated with higher levels of cognition, such as judgment, reasoning, and decision-making.

Following the Australopithecus, Homo habilis saw a further increase in brain size and a structural expansion in the area of the brain associated with expressive language. Gradually, the brain development reached and stabilized in the range of its modern measurements, those of early Homo sapiens. The regions of the brain that completed their growth at that stage were those associated with planning, communication, and advanced cognitive functions, while the prefrontal areas, that are bigger in humans than in other apes, affected planning, language, attention, social information processing, temporal information processing, namely improvisational intelligence.

Information processing has been a guiding aspect of human evolution, fundamentally structured around acquiring sensory input from the environment and then interpreting and organizing it by the brain. A brain may be referenced in function to a computer in that both are types of computing machines generating complex patterns of output, after dissemination of correlating complex patterns of input, and after querying to stored information. Such organizational structure can be affected by our 'in-flow data filter' that regulates how much attention we pay our surroundings, without overloading our systems. For instance, when you engage in a conversation in a public place, your brain filters out background noise focusing your sensory input acquisition on the required interactive action. So-to-speak attention algorithms can be determined by you voluntarily in what is known as top-down processing or it may be automatic, in what is known as bottom-up processing. Recurrently, most of the external data that our brain captures and uses is not completely conscious. In many instances, we make decisions influenced by information with no conscious awareness. And there is an evolutionary basis for this attentional choice among many others.

The best associating indicators of intelligence could be connected with the simpler but less predictable problems that animals encounter, novel situations where evolution has not provided a standard blueprint and the animal has to improvise by using its intellectual wherewithal. While humans often use the term intelligence to define both a broad spectrum of abilities and the efficiency with which they're deployed, it also implies flexibility and creativity, an "ability to slip the bonds of instinct and generate novel solutions to problems" (Gould and Gould, 1994). 

Human behavior is the most astonishingly flexible behavior among any animal species. Heuristic intelligence, or improvisational intelligence, is the exemplary core for a phenomenon of human behavior in the evolutionary cognitive process. Heuristics are rules-of-thumb and simplified cognitive shortcuts we use to arrive at decisions and conclusions, helping us save energy and processing power. Cosmides and Tobby (2002) divide intelligences into two distinct categories: dedicated intelligences and improvisational intelligences, wherein dedicated intelligence refers to "the ability of a computational system to solve predefined, target set of problems" and improvisational intelligence refers to “the ability of a computational system to improvise solutions to novel problems”. They argue that the latter form of reasoning is employed whenever al allocated processing module doesn't exist to solve a particular problem. Our computational brain hierarchy is composed of a structure of innate neural networks, which have distinct established evolutionary developed functions, or massive modularity. The mind is not composed of "general-purposes" mechanisms, such as a general-purpose reasoning mechanism or a general-purpose learning mechanism, but instead consists of hundreds or thousands of highly specialized modules that provide us with innate knowledge and innate abilities in various sporadic domains. Most of these modules evolved during human development time in Pleistocene hunter-gatherer societies, applying universality over all human populations. They constitute an invariant human nature.

Within such modularity, improvisational intelligence essentially conceives a more domain-general kind of intelligence as being 'bundled-together' of several dedicated intelligences to solve evolutionary novel problems such as driving cars, using smartphones or launching rockets to space. Improvisational intelligence enables humans to solve such novel problems by processing information that is transiently and contingently valid. It is designed to represent the unique features of particular combinations of evolutionary recurrent categories and requires mechanisms that translate data from dedicated intelligences into common standards. Modular adaptations are invariably by specific external stimuli and improvisational intelligence, by contrast, permits the use of knowledge derived from domain specific inference systems in the absence of triggering stimuli. Hence, humans, unlike existing today machines embedded with artificial intelligence, are able to reason about the consequences of what is unknown, what can be anticipated to become known in the future or what is not physically present.

But is there a way to bootstrap improvisational intelligence and incorporate improvisation mechanisms? Non-evalutionary improvisation must be only memory-based as an emergent process guided by the expanding collection of background knowledge. Learning in the current context of machine learning is like querying an expert for an answer - an independent and purposeful activity in itself, the end product being newly created knowledge. In artificial agents case, by bundling novel memory (the ability to retrieve relevant background knowledge) and novel analogical reasoning (the ability to transfer knowledge from a similar situation in the past to the current situatio) of artificial non-evolutionary intelligent systems are fundamental to novel problem reformulation, which in turn is the basis for improvisational intelligence. The further humans extend their existence, subsequently unlinking evolution-based dedicated intelligences, the higher are chances for intelligent agents to establish human-like improvisational intelligence.